System, method and computer program product for contextual focus/zoom of event celebrities

ABSTRACT

A contextual zoom control method, system, and computer program product, includes detecting faces in an area of interest when a user is performing an image capturing action, extracting a facial image for each of a set of key individuals attending an event where the user is performing the image capturing action, creating a ranked list of the set of key individuals according to a predetermined parameter of each key individual, pairing each detected face with a matching extracted facial image to label an identity of each key individual in the area of interest, and in a single individual capturing mode, performing a camera function to assist the user in performing the image capturing action on the identity that is paired with a highest ranked individual on the ranked list within the area of interest.

BACKGROUND

The present invention relates generally to a contextual zoom controlmethod, and more particularly, but not by way of limitation, to asystem, method, and computer program product for assistingphotographers, using smart phones and/or smart cameras for taking aphotograph, in selecting a celebrity on which to (contextually) zoomtheir camera lens focus.

Capturing photographs of celebrities is one of the most significantactivities that happens every day with a camera (including smartphones).Most of the individuals go to shows, sports events, concerts, theatersand so on, with their smartphones and at times smart cameras, andattempt to capture pictures of the celebrities that perform on the show,or make guest appearances (on shows, near the shows on the VIP seats orreserved areas, etc.).

Conventionally, camera focus/zoom techniques are well-known. However,such techniques are context-agnostic and the target person'sidentity-agnostic.

SUMMARY

In an exemplary embodiment, the present invention can provide acomputer-implemented contextual zoom control method, the methodincluding detecting faces in an area of interest when a user isperforming an image capturing action, extracting a facial image for eachof a set of key individuals attending an event where the user isperforming the image capturing action, creating a ranked list of the setof key individuals according to a popularity of each key individual,pairing each detected face with a matching extracted facial image tolabel an identity of each key individual in the area of interest, and ina single individual capturing mode, performing a camera function toassist the user in performing the image capturing action on the identitythat is paired with a highest ranked individual on the ranked listwithin the area of interest.

One or more other exemplary embodiments include a computer programproduct and a system.

Other details and embodiments of the invention will be described below,so that the present contribution to the art can be better appreciated.Nonetheless, the invention is not limited in its application to suchdetails, phraseology, terminology, illustrations and/or arrangements setforth in the description or shown in the drawings. Rather, the inventionis capable of embodiments in addition to those described and of beingpracticed and carried out in various ways and should not be regarded aslimiting.

As such, those skilled in the art will appreciate that the conceptionupon which this disclosure is based may readily be utilized as a basisfor the designing of other structures, methods and systems for carryingout the several purposes of the present invention. It is important,therefore, that the claims be regarded as including such equivalentconstructions insofar as they do not depart from the spirit and scope ofthe present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the invention will be better understood from the followingdetailed description of the exemplary embodiments of the invention withreference to the drawings, in which:

FIG. 1 exemplarily shows a high-level flow chart for a contextual zoomcontrol method 100 according to an embodiment of the present invention;

FIG. 2 exemplarily depicts an exemplary system 200 diagram according toan embodiment of the present invention;

FIG. 3 depicts a cloud-computing node 10 according to an embodiment ofthe present invention;

FIG. 4 depicts a cloud-computing environment 50 according to anembodiment of the present invention; and

FIG. 5 depicts abstraction model layers according to an embodiment ofthe present invention.

DETAILED DESCRIPTION

The invention will now be described with reference to FIGS. 1-5, inwhich like reference numerals refer to like parts throughout. It isemphasized that, according to common practice, the various features ofthe drawing are not necessarily to scale. On the contrary, thedimensions of the various features can be arbitrarily expanded orreduced for clarity.

By way of introduction of the example depicted in FIG. 1, an embodimentof a contextual zoom control method 100 according to the presentinvention can include various steps for assisting photographers, usingsmart phones and/or smart cameras for taking a photograph, in selectingcelebrities on which to (contextually) zoom their camera lens focus,when an attempt of a user to zoom onto an expected celebrity presentnearby in the same location is detected, with a potential intent toclick a photograph of the celebrity (and optionally auto-click thepicture too). By way of introduction of the example depicted in FIG. 2,one or more computers of a computer system 12 according to an embodimentof the present invention can include a memory 28 having instructionsstored in a storage system to perform the steps of FIG. 1.

Thus, a contextual zoom control method 100 according to an embodiment ofthe present invention may act in a more sophisticated, useful andcognitive manner, giving the impression of cognitive mental abilitiesand processes related to knowledge, attention, memory, judgment andevaluation, reasoning, and advanced computation. In other words, a“cognitive” system can be said to be one that possesses macro-scaleproperties—perception, goal-oriented behavior, learning/memory andactions generally recognized as cognitive.

Although one or more embodiments may be implemented in a cloudenvironment 50 (see e.g., FIG. 3), it is nonetheless understood that thepresent invention can be implemented outside of the cloud environment.

In the description herein, the term “camera function” refers to a zoomfunction, a focus function, red-eye elimination function, flashfunction, etc. that a camera can perform. Further, it is noted that“zoom” and “focus” are used interchangeably and refer to an automatedaction that the camera takes to either zoom on a face or focus a face inthe image. Also, “an area of interest” refers to the imaging view screenof the camera device and the area that the image is capturing.

Referring now to FIG. 1, in step 101, faces in an area of interest whena user if performing an image capturing action are detected. That is,the user's intent to capture a photograph is detected, by the user'saction of switching on the camera (or the smartphone's cameraapplication or smart camera). Further, the approximate area of interestof the user to capture the photograph is detected, by the manualmovement and attempt to set the focus of the camera. The area ofinterest corresponds to the area in which the user is taking the image.As the user zooms the he camera onto a location or attempts to focus thearea of interest, faces of the individuals in the area of interest aredetected using facial recognition software, by taking hidden images(e.g., not shown to the user and only saved in metadata), etc. One ormore faces are detected from the area of interest and the faces aretreated as a first input set “i₁” (as described later).

In step 102, a facial image is extracted for each of a set of keyindividuals attending an event where the user is performing the imagecapturing action. That is, the most likely event is extracted as well asa facial image for a set of key individuals (e.g., such as celebrities)expected to participate in the event are detected using a context of theevent (e.g., location and current time), a search process is conductedon a public search engine (such as Google, Bing etc.) as well as socialnetworks (such as Twitter, Facebook, Instagram, etc.), and using naturallanguage processing techniques (NLP) for the program of the event (e.g.,in a case that the event venue publishes any information, then thatinformation is also processed to find the expected individuals(including celebrities) to participate in the program). In other words,the celebrities at an event are identified and a facial image for eachof the celebrities is data mined.

In step 103, a ranked list of the set of key individuals is createdaccording to a predetermined parameter (e.g., popularity of eachindividual). For example, if five celebrities are attending the event,the five celebrities are ranked from first to fifth according topopularity. That is, when multiple celebrities are detected in step102/103, a popularity ranking technique is invoked (such as, a webkeyword popularity technique, or external data feed sources).“Popularity” also may be measured by a number of google hits associatedwith the identity of the person, a number of articles published by theperson, a number of newspaper articles on the person, etc. It is notedthat instead of popularity, another parameter could be used to rankindividuals such as notoriety (e.g., a notorious individual may not bepopular), a documented success, a net worth, etc.

It is noted that in step 102 and step 103, the facial image of eachparticipating celebrity is extracted in step 102 and associated with theranked list created in step 103. The association of the facial image toa celebrity and their corresponding popularity rank is treated as secondinput set “i₂”.

In step 104, each detected face from step 101 is paired with a matchingextracted facial image from step 102 to label an identity of the personin the area of interest. In other words, each face in the area ofinterest is paired with a facial image, then the identity of the facialimage paired with the face is confirmed as the identity of theindividual. For example, if a face in the area of interest matches witha facial image of Barack Obama, the identity of the individual islabeled as “Barack Obama”. In this manner, the identity of thecelebrities in the area of interest is labeled in order to perform acamera function (as described later).

That is, in step 104, the first input “i₁” and second input “i₂” arematched, and a ranked list of celebrities present in the set “i₁” isoutput, where the ranking is based upon a combination (apolicy-dependent function) of the popularity of the celebrity and theproximity of the user's camera's center of focus to the set ofcelebrities visible within the focus-zone of the camera.

In step 105, the camera is selectively (optionally) utilizing a singleindividual capturing mode. The single individual capturing modeindicates that the user would like to zoom/focus only on a singlecelebrity in the area of interest of the image. Therefore, in step 105,a camera function is performed to assist the user in performing theimage capturing action on the identity that is paired with a highestranked individual on the ranked list within the area of interest. Inother words, step 105 causes the camera to zoom in (or focus on) on themost popular celebrity within the area of interest. In this manner, theuser merely must point their camera in a direction of the desiredcelebrity they wish to photograph and the camera automatically zooms andfocuses on the celebrity.

In some embodiments, in step 105, the user is requested to select whichcelebrity on the ranked list on which the user would like the camerafunction to be performed. For example, the ranked list can be displayedon a display screen of the camera device as a graphical user interface(GUI) and the user can select which celebrity on the list they wouldlike to have imaged. Thus, the user can select any celebrity on the listregardless of the ranking.

In other embodiments, the user can confirm that the identity of theindividual is correct based on which individual is imaged. In thismanner, the method can act as a “cognitive” method and become smarterover iterations of the method in which the correlation betweenindividuals and faces is improved with user feedback. For example, ifthe camera function is performed on a non-important individual (i.e.,not a celebrity), then the user can return this feedback.

Thus, if the user uses a “single individual capturing mode”, then thecamera can help the user zoom on the first entity on the list, and ifthe user indicates that to be not the desired target (e.g., by pressinga button showed on screen, etc.) then the camera can help the user zoomon to the second entity on the list, and so on.

In step 106, the camera is utilizing a multi-individual capturing mode.The multi-individual capturing mode indicates that the user would liketo zoom/focus on a plurality of celebrities in the area of interest ofthe image. Therefore, in step 106, a camera function is performed toassist the user in performing the image capturing action on the identityof a user-specified number of individuals that are paired with theuser-specified number of highest ranked individuals on the ranked listwithin the area of interest. In other words, if the user specifies thatthey want “n” number of individuals in their image, the camera functionis performed such that the “n” number of highest ranked popularcelebrities are within the area of interest after the zoom/focusfunction is performed. For example, if two celebrities are standing sideby side, the single individual capturing mode only captures the mostpopular of the two. However, if the user indicates that they would liketo capture two celebrities, both celebrities would be within the area ofinterest after the camera function is performed.

In some embodiments, the user does not need to specify the number ofindividuals for the multi-individual capturing mode and instead thenumber of individuals is based on a popularity factor of the individualsbeing above a predetermined threshold value. For example, each celebritycan be assigned a popularity value in the ranked list. The number ofindividuals to perform the camera function and keep within the area ofinterest can be based on the number of celebrities in the area ofinterest being above a predetermined threshold.

Thus, if the user uses a “multi-individual capturing mode” and specifiesthe maximum number of celebrities “n” she wants within the focus area,then the camera will search for the top “n” (or lesser number of)celebrities (the argmax) within the focus area where the combinationfunction of the user's camera's center of focus and the popularity ofthe celebrity gives a maxima.

In some embodiments, the system 200 can execute the method 100 thereon.For example, a user 260 can use their smartphone 250 and a user's intentto click photograph detector 201 and photo zone detector 202 can detectfaces in an area of interest when the user is performing an imagecapturing action. At this point the implicit photograph series trigger203 begins imaging (or activating a facial recognition software) withinthe area of interest and the face set detector from the photographseries 204 extracts the faces within the area of interest.

At the same point, when the user is using the imaging device 250, theevent related documents and other information finder 206, the likelyevent and entity information extractor 207, and the celebrity photographfinder 209 extract a facial image for each of a set of key individualsattending an event where the user is performing the image capturingaction from the internet data 270, the social networks 280, and theevent database 290. Also, the contextual celebrity ranker 208 creates aranked list of the set of key individuals according to a popularity ofeach individual.

The photograph-to-face-set matcher/mapper 210 pairs the faces within thearea of interest to the facial images extracted by the celebrityphotograph finder 209 to label an identity of the person in the area ofinterest.

The zoom target set detector 211 interacts with the focus zoomassistance 205 on the smartphone 250 to either perform the singleindividual capturing mode or the multi-individual capturing modedescribed above in steps 105 and 106.

Thereby, the system 200 and associated method 100 can assistphotographers, using smart phones and/or smart cameras for taking thephotograph, in selecting celebrities to (contextually) zoom their cameralens focus on, when an attempt of an user to zoom onto an expectedcelebrity present nearby in the same location is detected, with apotential intent to click a photograph of the celebrity (and optionallyauto-click the picture too). That is, the invention may be useful insettings where the photographer is located within the same (and visible)zone as the celebrity, but is far enough away that a zoom of camerafocus is needed to get a good-quality picture, and optionally there aremultiple faces available around the zooming zone.

For example, when a whole basketball team is present together on theground (e.g., queueing up just before a match), and a spectator carryinga smartphone wants to capture a photo of the face of Stephan Curryrather than of the entire team, the spectator can indicate this intentto the system and the system in return will help the spectator identifyand zoom the focus onto Stephan Curry (and optionally, auto-click apicture of Stephan Curry as well).

In one embodiment, a user is attending the Flushing Meadows tennisstadium in New York to watch the United States Open Tennis Championshipsand it is the final match, with Novak Djokovic facing Roger Federer. Theuser tries focus his smart camera to on Novak Djokovic, to get aphotograph. An “intent to click photograph” action is triggered (e.g.,step 101). Djokovic, his coach, the lineswoman visible in thebackground, a ball boy who is waiting nearby and an official, all are inthe camera focus, as the user tries to zoom the view of his smart cameraonto Novak (and is in a “single person focus mode” with his smartcamera). At this stage, the camera takes an implicit photograph of thisset of people and detects the faces (e.g., step 101). The smart cameraalso finds out the location from a Global Positioning System (GPS), anduses the GPS as well as the current time of the day to find the currentevent name, thereby understanding that Roger Federer and Novak Djokovicare two key people present in the event. In step 102, photographs(pictures) of Roger Federer and Novak Djokovic are searched for andretrieves a set of pictures of faces of these two celebrities. Now, animage match technique is conducted for the faces within the area ofinterest and the pictures retrieved of the celebrities, and it is foundthat the face of Novak Djokovic is the match (e.g., step 103). Thecamera assists the user to focus onto Novak Djokovic, and optionallyauto-clicks one or more photos of Novak Djokovic also.

In the multi-individual capturing mode, the user attempts to take apicture of Roger and Novak, when they are near the net for the toss, butthe umpire is between them when viewed from the zone where the user istrying to get the photo from (his seat in the stadium)—however, the boyassisting the umpire is beside Roger. The faces are paired with matchingpictures of each of Roger and Novak to label their identity and then thecamera zooms and/or focuses on Roger and Novak to obtain the bestpossible image even if the image includes the umpire between them. Thatis, the multi-individual capturing mode maximizes the view score wherethe focus combiner Roger, Novak and the umpire, but excludes theassisting boy. It is noted that if the assisting boy were a differentcelebrity tennis player who was ranked third on the popularity list andthe user specified that they would like only two individuals imaged, thedifferent celebrity tennis player would also be excluded. Also, if thedifferent celebrity tennis player was more popular on the ranked listthan Roger and Novak, the camera function would zoom or focus on thedifferent tennis player and the more popular of Roger and Novak.

It is noted that the examples above dealt with the most popular tennisplayers. However, the invention is not limited thereto. That is, ifanother celebrity (e.g., Paul McCartney) was present and he was higheron the popularity list, in a single mode Paul McCartney (or the mostpopular of the people) would be pictured.

Also, the embodiments herein refer generally to popularity ranking.However, a user can specify the ranking mode such as based onpopularity, notoriety, net worth, platinum records, etc.

Exemplary Aspects, Using a Cloud Computing Environment

Although this detailed description includes an exemplary embodiment ofthe present invention in a cloud computing environment, it is to beunderstood that implementation of the teachings recited herein are notlimited to such a cloud computing environment. Rather, embodiments ofthe present invention are capable of being implemented in conjunctionwith any other type of computing environment now known or laterdeveloped.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client circuits through athin client interface such as a web browser (e.g., web-based e-mail) Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 3, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablenode and is not intended to suggest any limitation as to the scope ofuse or functionality of embodiments of the invention described herein.Regardless, cloud computing node 10 is capable of being implementedand/or performing any of the functionality set forth herein.

Although cloud computing node 10 is depicted as a computer system/server12, it is understood to be operational with numerous other generalpurpose or special purpose computing system environments orconfigurations. Examples of well-known computing systems, environments,and/or configurations that may be suitable for use with computersystem/server 12 include, but are not limited to, personal computersystems, server computer systems, thin clients, thick clients, hand-heldor laptop circuits, multiprocessor systems, microprocessor-basedsystems, set top boxes, programmable consumer electronics, network PCs,minicomputer systems, mainframe computer systems, and distributed cloudcomputing environments that include any of the above systems orcircuits, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingcircuits that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage circuits.

Referring now to FIG. 3, a computer system/server 12 is shown in theform of a general-purpose computing circuit. The components of computersystem/server 12 may include, but are not limited to, one or moreprocessors or processing units 16, a system memory 28, and a bus 18 thatcouples various system components including system memory 28 toprocessor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further described below, memory 28 mayinclude a computer program product storing one or program modules 42comprising computer readable instructions configured to carry out one ormore features of the present invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may be adapted for implementation in anetworking environment. In some embodiments, program modules 42 areadapted to generally carry out one or more functions and/ormethodologies of the present invention.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing circuit, other peripherals,such as display 24, etc., and one or more components that facilitateinteraction with computer system/server 12. Such communication can occurvia Input/Output (I/O) interface 22, and/or any circuits (e.g., networkcard, modem, etc.) that enable computer system/server 12 to communicatewith one or more other computing circuits. For example, computersystem/server 12 can communicate with one or more networks such as alocal area network (LAN), a general wide area network (WAN), and/or apublic network (e.g., the Internet) via network adapter 20. As depicted,network adapter 20 communicates with the other components of computersystem/server 12 via bus 18. It should be understood that although notshown, other hardware and/or software components could be used inconjunction with computer system/server 12. Examples, include, but arenot limited to: microcode, circuit drivers, redundant processing units,external disk drive arrays, RAID systems, tape drives, and data archivalstorage systems, etc.

Referring now to FIG. 4, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing circuits used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingcircuit. It is understood that the types of computing circuits 54A-Nshown in FIG. 4 are intended to be illustrative only and that computingnodes 10 and cloud computing environment 50 can communicate with anytype of computerized circuit over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring now to FIG. 5, an exemplary set of functional abstractionlayers provided by cloud computing environment 50 (FIG. 4) is shown. Itshould be understood in advance that the components, layers, andfunctions shown in FIG. 5 are intended to be illustrative only andembodiments of the invention are not limited thereto. As depicted, thefollowing layers and corresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage circuits 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and contextual zoom control method 100 inaccordance with the present invention.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

Further, Applicant's intent is to encompass the equivalents of all claimelements, and no amendment to any claim of the present applicationshould be construed as a disclaimer of any interest in or right to anequivalent of any element or feature of the amended claim.

1. A computer-implemented contextual zoom control method, the methodcomprising: detecting faces in an area of interest when a user isperforming an image capturing action; extracting a facial image for eachof a set of key individuals attending an event where the user isperforming the image capturing action; creating a ranked list of the setof key individuals according to a predetermined parameter of each keyindividual; pairing each detected face with a matching extracted facialimage to label an identity of each key individual in the area ofinterest; and in a single individual capturing mode, performing a camerafunction to assist the user in performing the image capturing action onthe identity that is paired with a highest ranked individual on theranked list within the area of interest, wherein the camera functionincludes at least one of a zoom function and a focus function.
 2. Thecomputer-implemented method of claim 1, further comprising, in amulti-individual capturing mode, performing a camera function to assistthe user in performing the image capturing action on the identity of auser-specified number of individuals that are paired with theuser-specified number of highest ranked individuals on the ranked listwithin the area of interest.
 3. (canceled)
 4. The computer-implementedmethod of claim 1, wherein the set of key individuals attending theevent are determined by any of data mining a context of the event, asearch engine, a social media source, and using natural languageprocessing on a published program of the event.
 5. Thecomputer-implemented method of claim 1, wherein the extracting extractsthe facial image by determining a list of the key individuals attendingthe event and then discovering the facial image for each of the keyindividuals attending the event.
 6. The computer-implemented method ofclaim 1, wherein each extracted facial image is correlated with anidentity of the key individual such that the identity of the detectedfaces can be determined when the detected faces are paired with amatching extracted facial image.
 7. The computer-implemented method ofclaim 1, wherein the image capturing action includes at least one of:orienting an imaging device in a manner consistent with a potentialintent to capture an image; and executing an imaging application on theimaging device.
 8. The computer-implemented method of claim 1, wherein,in response to performing the camera function in the single individualcapturing mode, requesting that the user submit a feedback on anaccuracy of the imaged individual, and wherein, if the feedbackindicates an inaccurate imaged individual, the method further comprisedisplaying a graphical user interface on the area of interest includingeach identity of the set of key individuals within the area of interestsuch that the user can select the identity of the set of key individualson which to perform the camera function.
 9. The computer-implementedmethod of claim 8, wherein, in response to performing the camerafunction in the single individual capturing mode, requesting that theuser submit a feedback on an accuracy of the imaged individual, andwherein, if the feedback indicates an inaccurate imaged individual,proceeding to perform the camera function to assist the user inperforming the image capturing action on the identity that is pairedwith a second highest ranked individual on the ranked list within thearea of interest.
 9. (canceled)
 10. The computer-implemented method ofclaim 1, embodied in a cloud-computing environment.
 11. A computerprogram product for contextual zoom control, the computer programproduct comprising a non-transitory computer readable storage mediumhaving program instructions embodied therewith, the program instructionsexecutable by a computer to cause the computer to perform: detectingfaces in an area of interest when a user is performing an imagecapturing action; extracting a facial image for each of a set of keyindividuals attending an event where the user is performing the imagecapturing action; creating a ranked list of the set of key individualsaccording to a predetermined parameter of each key individual; pairingeach detected face with a matching extracted facial image to label anidentity of each key individual in the area of interest; and in a singleindividual capturing mode, performing a camera function to assist theuser in performing the image capturing action on the identity that ispaired with a highest ranked individual on the ranked list within thearea of interest, wherein the camera function includes at least one of azoom function and a focus function.
 12. The computer program product ofclaim 11, further comprising, in a multi-individual capturing mode,performing a camera function to assist the user in performing the imagecapturing action on the identity of a user-specified number ofindividuals that are paired with the user-specified number of highestranked individuals on the ranked list within the area of interest. 13.(canceled)
 14. The computer program product of claim 11, wherein the setof key individuals attending the event is determined by any of datamining a context of the event, a search engine, a social media source,and using natural language processing on a published program of theevent.
 15. The computer program product of claim 11, wherein theextracting extracts the facial image by determining a list of the keyindividuals attending the event and then discovering the facial imagefor each of the key individuals attending the event.
 16. The computerprogram product of claim 11, wherein each extracted facial image iscorrelated with an identity of the key individual such that the identityof the detected faces can be determined when the detected faces arepaired with a matching extracted facial image.
 17. The computer programproduct of claim 11, wherein the image capturing action includes atleast one of: orienting an imaging device in a manner consistent with apotential intent to capture an image; and executing an imagingapplication on the imaging device.
 18. A contextual zoom control system,said system comprising: a processor, and a memory, the memory storinginstructions to cause the processor to perform: detecting faces in anarea of interest when a user is performing an image capturing action;extracting a facial image for each of a set of key individuals attendingan event where the user is performing the image capturing action;creating a ranked list of the set of key individuals according to apredetermined parameter of each key individual; pairing each detectedface with a matching extracted facial image to label an identity of eachkey individual in the area of interest; and in a single individualcapturing mode, performing a camera function to assist the user inperforming the image capturing action on the identity that is pairedwith a highest ranked individual on the ranked list within the area ofinterest, wherein the camera function includes at least one of a zoomfunction and a focus function.
 19. The system of claim 18, wherein thememory further stores instructions to cause the processor to perform, ina multi-individual capturing mode, a camera function to assist the userin performing the image capturing action on the identity of auser-specified number of individuals that are paired with theuser-specified number of highest ranked individuals on the ranked listwithin the area of interest.
 20. The system of claim 18, embodied in acloud-computing environment.
 21. The computer-implemented method ofclaim 8, wherein, if the feedback indicates an inaccurate imagedindividual, the method further comprise displaying a graphical userinterface on the area of interest including each identity of the set ofkey individuals within the area of interest such that the user canselect the identity of the set of key individuals on which to performthe camera function.
 22. The computer-implemented method of claim 5,wherein each extracted facial image is correlated with an identity ofthe key individual such that the identity of the detected faces can bedetermined when the detected faces are paired with a matching extractedfacial image.